How the Piotroski Score Can Make You a Better Investor

In 2000, Joseph Piotriski published a paper called “Value Investing: The Use of Historical Financial Statement Information to Separate Winners from Losers.” In this paper, he outlines a methodology, now known as the Piotroski Score, for increasing one’s investment returns by closely examining the historical financial information of companies.

Now, there are many articles available that describe what the Piotroski score is, and since there are mechanisms for calculating it automatically, we will cover it only briefly. In this article, we will dig into the underlying investment strategy and explain how it works.

Value investing is a well-known investing strategy that is followed by almost all of the famous investors. Benjamin Graham, of course, is the father of it, and Warren Buffet is one of his most famous disciples. Value investing, as the name implies, is focused on finding “cheap” companies – that is, companies who are trading at a low market price relative to their actual value. Price is not value. The trick is determining the underlying value.

One measure of value is book value. Book value is an accounting measure that represents the amount of money a company would have if it went out of business immediately. The book value is almost always less than the market value of a company, since companies are expected to have future earnings.

If you divide the market value by the book value, you get Price/Book, which is the ratio usually used for this comparison. When Price/Book = 1, the market believes the accounting value is accurate, and when Price/Book < 1, the market thinks the accounting value is too high. (Note: In Piotroski’s paper, he uses the term “BM” which is Book/Market, the reciprocal of Price/Book”.)

So, one great way to find undervalued companies is to find companies with a low Price/Book ratio. The problem with this approach is that there’s usually a very good reason why this ratio is low. Generally speaking, companies with a low Price/Book ratio are distressed. Directly after the financial crisis, for example, most banks had Price/Book values of less than one – primarily because of those toxic assets nobody could figure out.

The trick is to find companies that were distressed, but are now recovering, before the rest of the market finds them. If only there was some mechanism for determining the actual financial health of a company…

As you probably figured, the Piotroski score does just that. The score itself is a kind of ranking that ranges from zero to nine (nine being good). The number is the result of nine “signals” that measure three areas of financial condition: profitability, financial leverage, and operating efficiency. Embedded in these measures, however, is the concept of change. For example, if the company is making more cash this year than last, then it gets a point. In other words, companies with higher Piotroski scores are not just healthy, they are improving.

With that in mind, it becomes natural to think that combining the Price/Book and Piotroski Score measures in a stock screen could lead to some great finds.

In fact, Piotroski found that “an investment strategy that buys expected winners and shorts expected losers generates a 23% annual return between 1976 and 1996…” The American Association of Independent Investors (AAII) also reports phenomenal results from a Piotroski-based investment strategy.

So, the overall strategy is to find companies with a low Price/Book value but a high Piotroski score. Of course, there is a lot of room in here to get lost, but Piotroski offered one other excellent tidbit.

He stated that the companies with the best returns were smaller, thinly traded companies with no analyst coverage. The reason these types of companies tend to do better is because of the information gap – large companies that have a lot of analysts are going to have their financials pored over pretty regularly, so the chances of finding a mispricing will be much smaller. On the other hand, if one can find a small distressed company that is on the mend, it could represent an excellent opportunity.

Determining Investor Sentiment in Industries by Examining Institutional Funds Flow

One of the more interesting types of analysis available on Fintel is overall investment trends in industries. When doing analysis on individual securities, it is wise to examine the overall health of the company’s industry. Rising tides lift all boats, and the same can be said for securities.

Just like with companies, industry performance moves in cycles. As the performance of industries rise and fall, so does the investment. This phenomenon is called “sector rotation” and it is an important part of investing.

Fintel provides a tool that allows you to visualize the institutional funds flow into any industry. This allows investors to get a sense of the overall institutional sentiment of the industry, and to know whether money is pouring in, or pouring out.

What we do is examine the 13F filings made by every institution and cross-reference them against the self-reported SIC codes of every company that files with the SEC. We aggregate the total reported share and total reported value of these reports, and present them in a table and graph form. This allows investors to get a sense of the overall macro sentiment of an industry.

To see the industry sentiment, follow these steps.

1. Go to the Industry page and select the industry. For this example, I will select Gold and Silver Miners.

2. On the Gold and Silver Mining Page, select Investment Trend.

3. On the Investment Trend page, you will see a graph and a table of the reported shares and reported value of the investments.

ValueWalk Fund Tracker Widget

This is a quick demo that shows how to embed the ValueWalk Fund tracker on your web site. Use this code:
<iframe src="" width="1000" height="1800" frameborder="0" allowtransparency="true" border="0" scrolling="no"></iframe>

Activist Filing Tracker Widget

This is a quick demo that shows how to embed the Fintel activist tracker on your web site. Use this code:
<iframe src="" width="1000" height="600" frameborder="0" allowtransparency="true" border="0" scrolling="no"></iframe>

Why Build a Better Stock Screener?

A stock screener is simply a bit of technology that allows you to filter the securities on the market with some criteria in order to narrow our investing focus. There are a lot of stock screeners available already, so why build another one?

The reason is that they simply aren’t flexible enough.

Most stock screeners provide simple range filters — that is, expressions that allow you to select a predetermined filter term (“pe”) and a range of values (“< 15”). By combining a few of these filters (“pe < 15; MarketCap > 500M”), you are expected to get the results you need.

For most people, this is probably enough, but it’s too simplistic for me.

Let’s start with the very simplest of queries. What if I want to find all companies that have more cash that their market cap? This could be represented as a formula like this:

Cash > MarketCap

I challenge you to find any free stock screener that can perform this query.

Now let’s examine the most well known investing strategy on the planet. Benjamin Graham’s Net Net Working Capital strategy. The strategy simply says, buy companies when the Net Net Working Capital is less than 2/3 of the company’s market cap. This can be represented in the following formula, or in this screen.

Cash + 75%*AccountsReceivable + 50%*Inventory - Liabilities > MarketCap

This is not a particularly complex equation, but like our first example, it doesn’t fit into the simple form of x < 999.

By building a stock screener that allows analysts to screen the market using complex expressions, I hope to open up a new world of screening capabilities to the data-driven equity analyst.

Try out the stock screener now!